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## [1]   5 108

Visualization

Semester effect on adhd_total

## For one-way between subjects designs, partial eta squared is equivalent
##   to eta squared. Returning eta squared.
## # Effect Size for ANOVA
## 
## Parameter                 |     Eta2 |       95% CI
## ---------------------------------------------------
## days_since_semester_start | 7.02e-03 | [0.00, 1.00]
## 
## - One-sided CIs: upper bound fixed at [1.00].
## `geom_smooth()` using formula = 'y ~ x'

## `geom_smooth()` using formula = 'y ~ x'

## Scale for y is already present.
## Adding another scale for y, which will replace the existing scale.
## `geom_smooth()` using formula = 'y ~ x'

quick note: we do not have data for spring-2023

## `geom_smooth()` using formula = 'y ~ x'

enrollment number

## `summarise()` has grouped output by 'semester_id'. You can override using the
## `.groups` argument.

Semester effect on ADHD_clinical

## `geom_smooth()` using formula = 'y ~ x'

Semester effect on Agreeableness score

## For one-way between subjects designs, partial eta squared is equivalent
##   to eta squared. Returning eta squared.
## # Effect Size for ANOVA
## 
## Parameter                 |     Eta2 |       95% CI
## ---------------------------------------------------
## days_since_semester_start | 1.25e-03 | [0.00, 1.00]
## 
## - One-sided CIs: upper bound fixed at [1.00].
## `geom_smooth()` using formula = 'y ~ x'

## `geom_smooth()` using formula = 'y ~ x'

## `geom_smooth()` using formula = 'y ~ x'

## `geom_smooth()` using formula = 'y ~ x'

Semester effect on Conscientiousness score

## For one-way between subjects designs, partial eta squared is equivalent
##   to eta squared. Returning eta squared.
## # Effect Size for ANOVA
## 
## Parameter                 | Eta2 |       95% CI
## -----------------------------------------------
## days_since_semester_start | 0.01 | [0.01, 1.00]
## 
## - One-sided CIs: upper bound fixed at [1.00].
## `geom_smooth()` using formula = 'y ~ x'

## `geom_smooth()` using formula = 'y ~ x'

## `geom_smooth()` using formula = 'y ~ x'

## `geom_smooth()` using formula = 'y ~ x'

Semester effect on Neuroticism score

## For one-way between subjects designs, partial eta squared is equivalent
##   to eta squared. Returning eta squared.
## # Effect Size for ANOVA
## 
## Parameter                 |     Eta2 |       95% CI
## ---------------------------------------------------
## days_since_semester_start | 1.10e-04 | [0.00, 1.00]
## 
## - One-sided CIs: upper bound fixed at [1.00].
## `geom_smooth()` using formula = 'y ~ x'

## `geom_smooth()` using formula = 'y ~ x'

## `geom_smooth()` using formula = 'y ~ x'

## `geom_smooth()` using formula = 'y ~ x'

Semester effect on Openness score

## For one-way between subjects designs, partial eta squared is equivalent
##   to eta squared. Returning eta squared.
## # Effect Size for ANOVA
## 
## Parameter                 |     Eta2 |       95% CI
## ---------------------------------------------------
## days_since_semester_start | 4.93e-03 | [0.00, 1.00]
## 
## - One-sided CIs: upper bound fixed at [1.00].
## `geom_smooth()` using formula = 'y ~ x'

## `geom_smooth()` using formula = 'y ~ x'

## `geom_smooth()` using formula = 'y ~ x'

## `geom_smooth()` using formula = 'y ~ x'

Semester effect on Extraversion score

## For one-way between subjects designs, partial eta squared is equivalent
##   to eta squared. Returning eta squared.
## # Effect Size for ANOVA
## 
## Parameter                 |     Eta2 |       95% CI
## ---------------------------------------------------
## days_since_semester_start | 4.70e-03 | [0.00, 1.00]
## 
## - One-sided CIs: upper bound fixed at [1.00].
## `geom_smooth()` using formula = 'y ~ x'

## `geom_smooth()` using formula = 'y ~ x'

## `geom_smooth()` using formula = 'y ~ x'

## `geom_smooth()` using formula = 'y ~ x'

Semester effect on Growth Mindset Score

## For one-way between subjects designs, partial eta squared is equivalent
##   to eta squared. Returning eta squared.
## # Effect Size for ANOVA
## 
## Parameter                 |     Eta2 |       95% CI
## ---------------------------------------------------
## days_since_semester_start | 1.43e-05 | [0.00, 1.00]
## 
## - One-sided CIs: upper bound fixed at [1.00].
## `geom_smooth()` using formula = 'y ~ x'

## `geom_smooth()` using formula = 'y ~ x'

## `geom_smooth()` using formula = 'y ~ x'

## `geom_smooth()` using formula = 'y ~ x'

Semester effect on grit score

## For one-way between subjects designs, partial eta squared is equivalent
##   to eta squared. Returning eta squared.
## # Effect Size for ANOVA
## 
## Parameter                 |     Eta2 |       95% CI
## ---------------------------------------------------
## days_since_semester_start | 3.69e-03 | [0.00, 1.00]
## 
## - One-sided CIs: upper bound fixed at [1.00].
## `geom_smooth()` using formula = 'y ~ x'

## `geom_smooth()` using formula = 'y ~ x'

## `geom_smooth()` using formula = 'y ~ x'

## `geom_smooth()` using formula = 'y ~ x'

Semester effect on grit interest

## For one-way between subjects designs, partial eta squared is equivalent
##   to eta squared. Returning eta squared.
## # Effect Size for ANOVA
## 
## Parameter                 |     Eta2 |       95% CI
## ---------------------------------------------------
## days_since_semester_start | 1.69e-03 | [0.00, 1.00]
## 
## - One-sided CIs: upper bound fixed at [1.00].
## `geom_smooth()` using formula = 'y ~ x'

## `geom_smooth()` using formula = 'y ~ x'

## `geom_smooth()` using formula = 'y ~ x'

## `geom_smooth()` using formula = 'y ~ x'

Semester effect on grit effort

## For one-way between subjects designs, partial eta squared is equivalent
##   to eta squared. Returning eta squared.
## # Effect Size for ANOVA
## 
## Parameter                 |     Eta2 |       95% CI
## ---------------------------------------------------
## days_since_semester_start | 3.21e-03 | [0.00, 1.00]
## 
## - One-sided CIs: upper bound fixed at [1.00].
## `geom_smooth()` using formula = 'y ~ x'

## `geom_smooth()` using formula = 'y ~ x'

## `geom_smooth()` using formula = 'y ~ x'

## `geom_smooth()` using formula = 'y ~ x'

Semester effect on Overall Matrices Hit Rate

## For one-way between subjects designs, partial eta squared is equivalent
##   to eta squared. Returning eta squared.
## # Effect Size for ANOVA
## 
## Parameter                 |     Eta2 |       95% CI
## ---------------------------------------------------
## days_since_semester_start | 5.53e-03 | [0.00, 1.00]
## 
## - One-sided CIs: upper bound fixed at [1.00].
## `geom_smooth()` using formula = 'y ~ x'

## `geom_smooth()` using formula = 'y ~ x'

## `geom_smooth()` using formula = 'y ~ x'

## `geom_smooth()` using formula = 'y ~ x'

Semester effect on Sandia Matrices Hit Rate

## For one-way between subjects designs, partial eta squared is equivalent
##   to eta squared. Returning eta squared.
## # Effect Size for ANOVA
## 
## Parameter                 |     Eta2 |       95% CI
## ---------------------------------------------------
## days_since_semester_start | 2.63e-03 | [0.00, 1.00]
## 
## - One-sided CIs: upper bound fixed at [1.00].

Semester Effect in ucmrt hit rate

## For one-way between subjects designs, partial eta squared is equivalent
##   to eta squared. Returning eta squared.
## # Effect Size for ANOVA
## 
## Parameter                 |     Eta2 |       95% CI
## ---------------------------------------------------
## days_since_semester_start | 6.66e-03 | [0.00, 1.00]
## 
## - One-sided CIs: upper bound fixed at [1.00].

Thinking about how to visualize the questions

Try to think the way of representing revolution of performance(values for measures) over the semester, over each semester or over the year